Data in the form of a time-series is common in many fields, including science, engineering, and business. Analyzing one or more time-series can provide valuable insights. For example, operating engineers managing thousands of machines running different services in a cloud can monitor CPU usage and memory consumption of the machines. In order to improve resource allocation and capacity planning, operating engineers may collect and analyze one or more time-series of data points that represent CPU usage and memory consumption for one or more corresponding machines. Thus, an operating engineer may have many different time-series that represent CPU usage for many different machines. Due to the large amount of data associated with different time-series, an operating engineer may find it challenging to organize the data and to recognize patterns or similarities across many different machines.